Simultaneous-source acquisition involves recording two or more seismic shots over the same time interval. This increases acquisition efficiency, but in many circumstances, the recorded signals attributable to individual sources need to be separated in order to enable further data processing. Separation techniques are generally implemented in a domain containing data from many shots in order to take advantage of dithering. However, this means that the sampling is dependent on the shot interval, which is often large enough to cause problems due to spatial aliasing. Use of sparse inversion overcomes this to some extent, but the technique is still problematic if the shot interval is too large.
Conventional data (i.e., shots fired sequentially) with an undesirably-large shot interval are typically processed by interpolating shots between the acquired ones. Unfortunately, unseparated simultaneous-source data cannot be interpolated using algorithms designed for conventional data because the timing differences between shots for multiple sources (also sometimes referred to as a “dither”) create incoherency from shot to shot for at least one of the sources.
Accordingly, there is a need for methods and systems that can employ more effective and accurate methods for data processing of collected data that corresponds to a subsurface region, including techniques that allow separation of collected data, including simultaneous-source acquired data.